Abstract: Image recognition is a key research field of image processing. Under the influence of the difficult determination of test results and the unbalanced category of data set samples, the test technology suitable for the robustness and stability of image recognition systems is deficient. In order to effectively test the image recognition system, this paper applies metamorphosis test method into testing process of image recognition system, generates derived data close to reality based on Generative Adversarial Network to construct a metamorphic relationship suitable for the image recognition system, introduces derivative image quality verification methods and automatic judgment methods of test results to construc a metamorphic testing framework process for image recognition systems. Finally, the feasibility and effectiveness of this method are verified through a case study of vehicle identification. The experimental results show that the method can detect the inconsistent behavior of the image recognition system in different scenes and can evaluate the robustness of system effectively.

Key words: metamorphic testing, image recognition, GAN(Generative Adversarial Network)